Advances in statistical models for d...
Morlini, Isabella.

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  • Advances in statistical models for data analysis
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Advances in statistical models for data analysis/ edited by Isabella Morlini, Tommaso Minerva, Maurizio Vichi.
    other author: Morlini, Isabella.
    Published: Cham :Springer International Publishing : : 2015.,
    Description: viii, 268 p. :ill., digital ;24 cm.
    [NT 15003449]: Using the dglars Package to Estimate a Sparse Generalized Linear Model -- A Depth function for Geostatistical Functional Data -- Robust Clustering of EU Banking Data -- Sovereign Risk and Contagion Effects in the Eurozone: a Bayesian Stochastic Correlation Model -- Female Labour Force Participation and Selection Effect: Southern vs Eastern European Countries -- Asymptotics in Survey Sampling for High Entropy Sampling Design -- A Note On the Use of Recursive Partitioning in Causal Inference -- Meta-Analysis of Poll Accuracy Measures: A Multilevel Approach -- Families of Parsimonious Finite Mixtures of Regression Models -- Quantile Regression for Clustering and Modeling Data -- Non-metric MDS Consensus Community Detection -- The performance of the Gradient-like Influence Measure in Generalized Linear Mixed Models -- New Flexible Probability Distributions for Ranking Data -- Robust Estimation of Regime Switching Models -- Incremental Visualization of Categorical Data -- A new Proposal for Tree Model Selection and Visualization -- Object-Oriented Bayesian Network to Deal with Measurement Error in Household Surveys -- Comparing Fuzzy and Multidimensional Methods to Evaluate Well-being in European Regions -- Cluster Analysis of Three-way Atmospheric Data -- Asymmetric CLUster Analysis Based on SKEW-symmetry: ACLUSKEW -- Parsimonious Generalized Linear Gaussian Cluster-Weighted Models -- New perspectives for the MDC Index in Social Research Fields -- Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches -- Novelty Detection with One-class Support Vector Machines -- Using Discrete-time Multi-State Models to Analyze Students' University Pathways.
    Contained By: Springer eBooks
    Subject: Mathematical statistics. -
    Online resource: http://dx.doi.org/10.1007/978-3-319-17377-1
    ISBN: 9783319173771
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W9275064 電子資源 11.線上閱覽_V 電子書 EB QA276 .A244 2015 一般使用(Normal) On shelf 0
  • 1 records • Pages 1 •
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